Health Informatics: Practical Guide, Seventh Edition

By Robert E Hoyt and William R. Hersh

Health Informatics: Practical Guide focuses on the application of information technology in healthcare to improve individual and population health, education and research. The goal of the seventh edition is to stimulate and educate healthcare and IT professionals and students about the key topics in this rapidly changing field. Dr. William Hersh from Oregon Health & Science University is the co-editor and author of multiple chapters. Topics include Health Informatics (HI) overview, electronic health records, healthcare data analytics, health information exchange, architecture of information systems, evidence-based medicine, consumer health informatics, HI ethics, quality improvement strategies and more. The 22 chapters feature learning objectives, case studies, recommended reading, future trends, key points, conclusions and over 1800 references.

• Language: English
• Publisher: Lulu.com
• Release date: Jun 19, 2018
• ISBN: 9781387827503

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ROBERT E. HOYT • ELMER V. BERNSTAM • WILLIAM R. HERSH

During the past few decades the volume of medical knowledge has increased so rapidly that we are witnessing an unprecedented growth in the number of medical specialties and subspecialties. All these difficulties arise from the present, nearly unmanageable volume of medical knowledge and the limitations under which humans can process information.

—Marsden S. Blois, Information and Medicine: The Nature of Medical Descriptions, 1984

LEARNING OBJECTIVES

After reading this chapter the reader should be able to:

•State the definition and origin of health informatics

•Identify the drivers behind health informatics

•Describe the key people and organizations involved in health informatics

•Discuss the impact of the HITECH Act and Affordable Care Act on health informatics

•List the barriers to health information technology (HIT) adoption

•Describe educational and career opportunities in health informatics

INTRODUCTION

Health (or as originally called, medical) informatics emerged as a discipline in the 1960s but has only recently gained recognition as an important component of healthcare. Its emergence is partly due to the multiple challenges facing the healthcare system today. As the quote above indicates, the growth in the volume of medical knowledge and patient information that occurred due to better understanding of human health has resulted in more treatments and interventions that produce more information. Likewise, the increase in specialization has also created the need to share and coordinate patient information. Furthermore, clinicians need to be able to access medical information expeditiously, regardless of location or time of day. Technology has the potential to help with each of those areas.

With the advent of the Internet, high speed computers, voice recognition, wireless and mobile technologies, healthcare professionals today have many more tools at their disposal. However, in general, technology has been advancing faster than healthcare professionals can assimilate it into their practice of medicine. One could also argue that there is a critical limitation of current information technology that manages data and not information. Thus, there is a mismatch between what we need (i.e., tools to help us manage meaningful data = information) and what we have (i.e., effective tools for managing data, but ineffective tools to manage information). Additionally, given the volume of data and rapidly changing technologies, there is a great need for ongoing informatics education of all healthcare workers.

This chapter will present an overview of health informatics with emphasis on the factors that helped create and sustain this new field and the key players involved.

Data, Information, Knowledge and Wisdom Hierarchy

Informatics is the science of information and the blending of people, biomedicine and technology. Individuals who practice informatics are known as informaticians or informaticists. There is an information hierarchy that is important in the information sciences, as depicted in the pyramid in Figure 1.1. Notice that there is much more data than information, knowledge or wisdom. Not all data are meaningful, thus there is more data than information, knowledge or wisdom produced. The following are definitions to better understand the hierarchy:

•Data are symbols representing observations about the world. Data are the plural of datum (singular). Thus, a datum is the lowest level of representation, such as a number in a database (e.g., 5), or packets sent across a network (e.g., 10010100). There is no meaning associated with data; the 5 could represent five fingers, five minutes or have no real meaning at all. Modern computers store, manage, process and transmit data accurately and rapidly.

•Information is meaningful data or facts from which conclusions can be drawn by humans or computers. For example, five fingers has meaning in that it is the number of fingers on a normal human hand.

•Knowledge is information that is justifiably considered to be true. For example, an elevated fasting blood sugar level suggests an increased likelihood of diabetes mellitus.

•Wisdom is the critical use of knowledge to make intelligent decisions and to work through situations of signal versus noise. For example, a rising blood sugar can indicate diabetes and other secondary causes of hyperglycemia.

Figure 1.1: Information hierarchy

Ideally, health information technology (HIT) provides the tools to generate information from data that humans (clinicians and researchers) can turn into knowledge and wisdom.¹-² Thus, enabling and improving human decision making with usable information is a central concern of informaticians. This concept is discussed in much more detail in the chapter on healthcare data, information and knowledge.

The information sciences tend to promote data in formats that can be rapidly transmitted, shared and analyzed. Paper records and reports do not allow this, without a great deal of manual labor. The advent of electronic health records (EHRs) and multiple other healthcare information systems provided the ability and the need to collate and analyze large amounts of data to improve health and financial decisions. Figure 1.2 displays some of the common sources of health data.

Figure 1.2: Health Data Sources

(EHR=electronic health records, PHR=personal health record, HIE=health information exchange)

With ever increasing amounts of health-related data, we have seen the growth of new hardware, software and specialists to handle growing amounts of data. Enterprise systems have been developed that: integrate disparate information (clinical, financial and administrative); archive data; provide the ability to ‘mine’ data using business intelligence and analytic tools. This is discussed in more detail in the chapter on data mining and analytics and the chapter on data science. Figure 1.3 demonstrates a typical enterprise data system.

Figure 1.3: Enterprise data warehouse and data mining

DEFINITIONS OF INFORMATICS AND RELATED TERMS

Health informatics is the discipline concerned with management of healthcare data and information through the application of computers and other information technologies. It is more about applying information in the healthcare field than it is about technology per se. That is one of the many reasons it is different than pure information technology (IT) in a healthcare organization. Technology merely facilitates the collection, storage, transmission and analysis of data. Health informatics also includes data standards (such as HL7) and controlled medical vocabularies (such as SNOMED) that we will cover in the chapter on data standards. It also addresses issues of usability, clinical workflow, and other aspects of optimizing the use of data and information in healthcare.

Not only are there multiple definitions of health informatics, but there are other expressions of the term that use different adjectives before the noun informatics. For example, the premiere professional association for the field, the American Medical Informatics Association (AMIA), prefers the broader term biomedical informatics because it encompasses bioinformatics as well as medical, dental, nursing, public health, pharmacy, imaging and research informatics. Hersh uses the term biomedical and health informatics to describe the overarching field.³ (see Figure 1.4) Both AMIA and Hersh then subdivide the field with other terms based on the spectrum from cellular and molecular processes (bioinformatics) to the person (clinical informatics) to the population (public health informatics). Clinical informatics also focuses on informatics in the healthcare system and may be further subdivided into the healthcare discipline (nursing informatics, dental informatics, pathology informatics, etc.) or a focus on the consumer or patient (consumer health informatics). Hersh also adds broad categories that overarch the spectrum cell-person-population that are focused on images (imaging informatics) and research (research informatics).

Figure 1.4 Biomedical Informatics

One can also step back and define the word informatics itself. The origin of the term is attributed to Dreyfus in 1962.⁴ The word originally saw use in Europe, in particular France and Russia (informatique), and often was used synonymously with computer science. Hersh states that informatics is the discipline focused on the acquisition, storage, and use of information in a specific setting or domain.³ As such, one of the things that distinguishes informatics from information science and computer science is its rooting in a domain. The former School of Informatics at the State University of New York Buffalo defined informatics as the Venn diagram showing the intersection of people, information, and technology. Friedman has stated his "fundamental theorem" of biomedical informatics, which states that informatics is more about using technology to help people do cognitive tasks better than about building systems to mimic or replace human expertise.⁵

A historian of the field, Collen, states that the phrase medical informatics was first used in 1974.⁶ Although there are other disciplines that use the term informatics (legal informatics, chemoinfomatics, social informatics), its use is probably most prevalent in biomedicine and health.

There are also a number of frequently-cited definitions of biomedical (and health) informatics:

•" science of information, where information is defined as data with meaning. Biomedical informatics is the science of information applied to or studied in the context of biomedicine. Some, but not all of this information is also knowledge. " ⁷

•" scientific field that deals with biomedical information, data, and knowledge - their storage, retrieval, and optimal use for problem solving and decision making ." ⁸

The original term medical informatics has been replaced by other terms, including health informatics, usually to include the work of non-physician scientists (e.g., biologists) and practitioners (e.g., nurses) and even patients or consumers. The American Medical Informatics Association (AMIA) prefers the broader term biomedical informatics defined as "the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving and decision making, motivated by efforts to improve human health."⁹ Biomedical informatics is a multidisciplinary field, as it encompasses bioinformatics, genomics, computer science, cellular biology and the social and behavioral sciences. As we move closer to integrating human genetics into the day-to-day practice of medicine, this more global definition is increasingly relevant.

Some informatics-related terms are important to call out or elaborate:

Clinical Informatics is the sub-field of biomedical informatics that focuses on the level of a single individual. Physicians and non-physicians work in this field. For physicians, clinical informatics is the name of the new sub-specialty that allows board certification through the American Board of Preventive Medicine (and the American Board of Pathology for pathologists).¹⁰

Bioinformatics is the sub-field of biomedical informatics concerned with biological data, particularly that derived from genomics and the other omics, such as proteomics, metabolomics, and transcriptomics, although such data are increasingly linked to clinical, public health or other data.

There are also several other terms worth noting related to informatics:

Health information technology (HIT or health IT) is defined as the application of computers and technology in healthcare settings.

Health information management (HIM) traditionally focused on the paper medical record and coding. With the advent of the electronic health record (EHR), HIM specialists now must deal with a new set of issues, such as privacy and multiple new concepts such as voice recognition.

For a discussion of the definition, concepts and implications (e.g. distinguishing from other related fields), see the articles by Hersh3 and Bernstam, Smith and Johnson.⁷

BACKGROUND

Given the fact that most businesses incorporate IT into their enterprise fabric, one could argue that it was just a matter of time before the tectonic forces of medicine and IT collided. As more medical information was published and more healthcare data became available as a result of computerization, the need to automate, collect, archive and analyze data escalated. Also, as new technologies such as EHRs appeared, ancillary technologies such as disease registries, voice recognition and picture archiving and communication systems arose to augment functionality. In turn, these new technologies prompted the need for expertise in health information technology that spawned new specialties and careers.

Health informatics emphasizes information brokerage; the sharing of a variety of information back and forth between people and healthcare entities. Examples of medical information that needs to be shared include: lab results, x-ray results, vaccination status, medication allergy status, consultant’s notes and hospital discharge summaries. Medical informaticians harness the power of information technology to expedite the transfer and analysis of data, leading to improved efficiencies. The field also interfaces with other fields such as the health sciences, computer sciences, biomedical engineering, biology, library sciences and public health, to mention a few. Informatics training, therefore, must be expansive and in addition to the topics covered in the chapters of this book must include IT knowledge about networks and systems, database management, usability, process re-engineering, workflow analysis and redesign, quality improvement, project management, leadership, teamwork, implementation and training.

HIT facilitates the processing, transmission and analysis of information and interacts with many important functions in healthcare organizations and serves as a common thread (Figure 1.5). This is one of the reasons the Joint Commission created the management of information standard for hospital certification.¹¹

Figure 1.5: Information, information technology and healthcare functions

Many aspects of health informatics noted in Figure 1.5 are interconnected. To accomplish data collection and analysis there is the hospital information systems (HIS) that collects financial, administrative and clinical information and subsystems such as the laboratory information system (LIS) and radiology information systems (RIS), with the latter often called the picture archive and communication system (PACS). As an example, a healthcare organization might be concerned that too many of its diabetic patients are not well controlled and believes it would benefit by offering a disease management web portal. With a portal, patients can upload blood sugar and blood pressure results to a central server so diabetic educators and/or clinicians can analyze the results and make recommendations. They also have the option to upload physiologic parameters via their mobile devices. The following technologies and issues are involved with just this one initiative and covered in other chapters:

•The web-based portal involves consumer (patient) informatics and telemedicine.

•Use of a smart phone is an important type of mobile technology.

•Management of diabetes requires online medical resources, evidence-based medicine, clinical practice guidelines, disease management and an EHR with a disease registry.

•If the use of the diabetic web portal improves diabetic control, clinicians may be eligible for improved reimbursement, known as value-based reimbursement.

There are multiple motivations driving the adoption of health information technology, but the major ones are the need to:

•Increase the efficiency of healthcare (improve physician, nurse and overall healthcare productivity)

•Improve the quality (patient outcomes) of healthcare, resulting in improved patient safety

•Reduce healthcare costs

•Improve healthcare access with technologies such as telemedicine

•Improve communication, coordination and continuity of care

•Improve medical education for clinicians and patients

•Standardization of medical care

These technologies and systems are critical for healthcare to achieve what the Institute for Healthcare Improvement describes as the Triple Aim of healthcare, which is to improve the patient’s experience, improve the health of populations and reduce the cost of healthcare.¹² Each of these can benefit from intelligent use of data and information.

Over the past 40 years, there has been increasing recognition that some wide variations in practice cannot be justified on objective clinical grounds. For example, patients in some areas of the United States are undergoing more invasive procedures than similar patients in other areas. Thus, there has been a movement to standardize the care of common and expensive conditions, such as coronary artery disease, heart failure and diabetes. Clinical practice guidelines are one way to provide advice at the point of care and we will discuss this in more detail in the chapter on evidence-based medicine.

This textbook discusses the driving forces motivating informatics and their inter-relationships. In addition to the motivation to deliver more efficient, safer and less costly healthcare, there is the natural diffusion of technology which also exerts an influence. In other words, as technologies such as wireless and voice recognition become more common, easier to use and less expensive, they will have an inevitable impact or pressure on the practice of medicine. Technological innovations appear at a startling pace as stated by Moore’s Law:

the number of transistors on a chip will double approximately every two years.¹³

Moore’s Law describes the exponential growth of transistors in computers. Technology will continue to evolve at a rapid rate, but it is important to realize that it often advances in an asynchronous manner. For example, laptop computers have advanced greatly with excellent processor speed and memory, but their utility is limited by a battery life of roughly 6-8 hours. This is a significant limitation given the fact that most nurses now work eight to twelve-hour shifts, so short battery life is one factor that currently limits the utility of laptop computers in healthcare. This may be overcome with tablet computers or a new battery design.

Healthcare is also subject to shifts in technology. A good example would be mobile technology that was quickly adopted by a large percentage of the world’s population and is strongly competing with landlines and desktop PCs. Digital imaging and voice recognition could also be considered evolving technological innovations. We can expect more innovations in the future, and we can only hope they are associated with a lower, not higher price tag than existing technologies.

The EHR, covered in another chapter, could be considered the centerpiece of health informatics with its potential to improve patient safety, medical quality, productivity and data retrieval. EHRs are a focal point of most patient encounters currently. Multiple resources that are currently standalone programs are being incorporated or integrated into the EHR, e.g. electronic prescribing, physician and patient education, genetic profiles, patient portals, disease registries and artificial intelligence, to mention a few. It is anticipated that EHR use will eventually be shown to improve patient outcomes, such as morbidity and mortality because of clinical decision support tools that decrease medication errors and standardize care with embedded clinical guidelines. However, at present, because EHRs do not adequately support clinicians’ information needs and workflow, they do little to improve patient care and, in some cases, have been shown to reduce the quality of care.¹⁴ Informaticians will play a major role in helping to reverse this trend. Among other things, it will not be enough to simply store electronic data; it must be shared among disparate partners. We will address HIE (information sharing) in a later chapter.

The Importance of Data

One of the outcomes of EHRs, RISs, mobile technologies, and other systems is the voluminous amount of healthcare data. As pointed out by Steve Ballmer, past CEO of Microsoft, there will be an "explosion of data" because of automating and digitizing multiple medical processes.¹⁵ Newer technologies such as electronic prescribing and HIE will produce data that heretofore has not been available. This explains, in part, why technology giants such as Microsoft, Intel and IBM have entered the healthcare arena. As we begin mining medical data from entire regions or organizations we will be able to make much better evidence-based decisions. Increasing data has also created the new buzz word Big Data that has several definitions:

•Data so large it can’t be analyzed or stored on one computational unit ¹⁶

•Five Vs: the definition started with three Vs but has increased to five:

oVolume: massive amounts of data are being generated each minute

oVelocity: data is being generated so rapidly that it needs to be analyzed without placing it in a database

oVariety: roughly 80% of data in existence is unstructured so it won’t fit into a database or spreadsheet. There is tremendous variety, in terms of the data that could potentially be analyzed. However, to do this requires new training and tools.

oVeracity: current data can be messy with missing data and other challenges. Because of the very significant volume of data, missing data may be less important than in the past

oValue: data scientists now have the capability to turn large volumes of unstructured data into something meaningful. Without value, data scientists will drown in data and not information or knowledge. ¹⁷

The textbook will point out in other chapters that large organizations, such as Kaiser Permanente have the necessary IT tools and expertise, financial resources, leadership and large patient population to be able to make evidence-based decisions in almost all facets of medicine. Pooling data is essential because most practices in the United States are small and do not provide enough information on their own to show the kind of statistical significance we need to alter the practice of medicine.¹⁸

The US federal government understands the importance of data and information to make evidence-based medical decisions. In 2009, a Presidential Open Government Directive was issued for the heads of the government agencies to promote the publication of government information online, improve the quality of data and to promote transparency.¹⁹ Consistent with that policy Project Open Data and Data.gov were created to share data of interest to multiple communities.²⁰-²¹ HealthData.gov is part of this initiative and serves to make datasets from the federal agencies available to a multitude of interested parties, such as healthcare organizations, developers, researchers, etc. Datasets are available through categories: health, state, national, Medicare, hospital, quality, community and inpatient. Because of this initiative, a variety of applications, mashups and visualizations have been developed. As of mid-2017 there were 254 health-related data sets on the site.²²

The following are examples of other applications or programs producing health-related data:

•Community Health Status Indicators: summarizes the health of the 3,143 counties in the US. Counties are rated as better, moderate or worse, compared to peer counties ²³

•Child Growth Charts: CDC web site that provides percentile charts for children ²⁴

•Behavioral Risk Factor Surveillance System (CDC): telephone surveys that collect information about risk behaviors, chronic health conditions and preventive services ²⁵

•Births (CDC): is part of the national vital statistics system collects data from birth certificates ²⁶

•Mortality and deaths (CDC): lists the number of deaths for leading causes of death ²⁷

•National Survey of Older Americans: is part of HHS and surveys Americans 60 and older to determine use of elderly services ²⁸

•State Cancer Profiles: includes interactive maps and graphs of cancer trends at the county, state and national levels. ²⁹

The federal government continues to add new sources of health-related data available to the public, healthcare professionals and researchers. Health Datapalooza is an annual event launched because of the Health Data Initiative (HDI), sponsored by HHS and the National Academy of Medicine. This public-private partnership brings together disparate users of healthcare data, to improve healthcare quality and safety.³⁰ Additional data resources are discussed in several other chapters.

The most recent and significant event to affect the health information sciences in the United States was the multiple programs associated with the HITECH Act of 2009, discussed later in this chapter. The programs included substantial financial support for EHRs, HIE and a skilled HIT workforce.

The introduction of information technology into the practice of medicine has been tumultuous for many reasons. New technologies are expensive, they may negatively affect workflow (e.g., interacting with the computer rather than with patients and data entry after work) and require advanced training.³¹ Unfortunately, this type of training rarely occurs during medical or nursing school or after graduation. More healthcare professionals who are bilingual in technology and medicine will be needed to realize the potential of new technologies. Vendors, insurance companies and governmental organizations will also be looking for the same expertise.

HISTORICAL HIGHLIGHTS

Information technology has been pervasive in the field of Medicine for only about three decades, but its roots began in the 1950s.³² Since the earlier days the field has experienced astronomical advances in technology, to include, personal computers, high resolution imaging, the Internet, mobile technology and wireless, to mention only a few. In the beginning, there was no strategy or vision as to how to advance healthcare using information technology. Now, we have the involvement of multiple federal and private agencies that are plotting future healthcare reform, supported by health information technology. The following are some of the more noteworthy developments related to health information technology:

•Computers. The first electronic general-purpose computer (ENIAC) was released in 1946 and required 1,000 sq. ft. of floor space. Primitive computers such as the Commodore and Atari appeared in the early 1980s along with IBM’s first personal computer, with a total of 16K of memory. ³³ Ironically, not everyone saw the future popularity of personal computers. Ken Olson, the president and chairman of Digital Equipment Corporation said in 1977 "There is no reason anyone would want a computer in their home." ³⁴ There has been dramatic growth in global PC sales until 2011 and after that a slow decline, presumably due to widespread use of mobile technology. ³⁵

Computers were first theorized to be useful for medical diagnosis and treatment by Ledley and Lusted in the 1959 when they published Reasoning Foundations of Medical Diagnosis.³⁶ They reasoned that computers could archive and process information more rapidly than humans. The programming language known as Massachusetts General Hospital Multi-Programming System (MUMPS) was developed in Octo Barnett’s lab at Massachusetts General Hospital in the 1970s. MUMPS exists today in the popular EHR known as VistA, used by the Veterans Affairs medical system and Epic Systems Corporation.³⁷

•German scientist Gustav Wagner developed the first professional organization for informatics (German Society for Medical Documentation, Computer Science and Statistics) in 1949. ³⁸

•It is thought that the origin of the term medical informatics dates to the 1960s in France (Informatique Medicale). ³⁹

•MEDLINE is the National Library of Medicine’s bibliographic database that contains more than 24 million references in the biomedical sciences. In the mid-1960s MEDLINE and MEDLARS were created to organize the world’s medical literature. For older clinicians who can recall trying to research a topic using the multi-volume print text Index Medicus , this represented a quantum leap forward. ⁴⁰

•Artificial Intelligence is a term used when a machine demonstrates learning and/or problem solving. Artificial intelligence (AI) projects in medicine, such as MYCIN (Stanford University) and INTERNIST-1 (University of Pittsburgh), appeared in the 1970s and 1980s. ⁴¹ Since the 1960s, AI has had alternating periods where research flourished and where it floundered, known as "AI winters."¹⁴ Natural language processing (NLP) is a subarea of AI that has the potential to intelligently interpret free text.

•Internet. The development of the Internet began in 1969 with the creation of the government project ARPANET. ⁴² The World Wide Web (WWW or web) was conceived by Tim Berners-Lee in 1990 and the first web browser Mosaic appeared in 1993. ⁴³- ⁴⁴ The Internet is the backbone for digital medical libraries, HIE and web-based medical applications. Although the terms Web and Internet are often used interchangeably, the Internet is the network-of-networks consisting of hardware and software that connects computers to each other. The Web is a set of protocols (particularly related to HyperText Transfer Protocol or HTTP) that are supported by the Internet. Thus, there are many Internet applications (e.g. email) that are not part of the Web. This is discussed further in the chapter on computer and network architectures. By March 2017 there were more than 3.7 billion Internet users in the world. ⁴⁵

•Electronic Health Record. The EHR has been advocated since the 1970s and was formally recommended by the Institute of Medicine (now known as the National Academy of Medicine) in 1991. ⁴⁶ EHRs will be discussed in more detail in a later chapter.

•Mobile technology. The Palm Pilot personal digital assistant (PDA) appeared in 1996 as the first truly popular handheld computing device. ⁴⁷ PDAs loaded with medical software became standard equipment for residents in training in the 1990s. They have been supplanted by smartphones, such as the iPhone. Smartphones and tablets will be discussed in more detail in the chapter on mobile technology. The popularity of mobile technology is evidenced by the fact that beginning in 2011 smartphone sales exceeded the sale of personal computers. ⁴⁸ Gartner, the world’s largest information technology research analyst reported that 1.5 billion smartphones were sold in 2016. ⁴⁹

•Human Genome Project. In 2003, the Human Genome Project (HGP) was completed after thirteen years of international collaborative research. Mapping all human genes was one of the greatest accomplishments in scientific history. Finalizing a draft of the genome was the first step. What remains is making intelligent use of the data. In other words, we need to understand the difference between data (the code), information (what the code means) and knowledge (what we do with the information). ⁵⁰ Data from large databases will likely change the way we practice medicine in the future. The HGP will be discussed in the chapter on bioinformatics.

KEY USERS OF HEALTH INFORMATION TECHNOLOGY

HIT is important to all stakeholders in healthcare. HIT generates important data that is transmitted, visualized, analyzed and archived by those in the field of health informatics. There are many important users of HIT:

•Patient – the individual who receives healthcare, often called a consumer or citizen when they are well

•Provider – those who provide healthcare, e.g., physicians, nurses, allied health providers

•Purchaser – those who buy healthcare, usually employers or the government

•Payor – those who pay the healthcare system, i.e., the insurance companies and government

•Public health – protectors of the public’s health

These stakeholders have diverse applications of HIT that they use during the healthcare process, maintaining health, or conducting research.⁵¹

ORGANIZATIONS INVOLVED WITH HEALTH INFORMATICS

There are many types of organizations involved in health informatics. One way to classify them is professional/trade associations, government, and industry. The latter can be subdivided into healthcare and HIT industries. Both academia and industry also have associations that represent their interests and are typically non-profit. Another category of organization is public-private partnerships.

Professional and Trade Associations

There are many professional organizations in the field of biomedical and health informatics. Probably the premier organization is the American Medical Informatics Association (AMIA). The mission of AMIA is to advance the informatics professions relating to health and disease. To this end, it advances the use of health information and communications technology in clinical care and clinical research, personal health management, public health population, and translational science with the ultimate objective of improving health.⁹

There are several other professional organizations devoted to aspects of biomedical and health informatics. One is the Healthcare Information and Management Systems Society (HIMSS), which is commonly thought to represent industry in the health IT field with a focus on vendors and consultants.⁵²

The American Health Information Management Association (AHIMA), represents the health information management (HIM) profession.⁵³ The Association of Medical Directors of Information Systems (AMDIS), represents physician leaders in HIT⁵⁴ and the Alliance for Nursing Informatics is a coalition that focuses on nursing informatics.⁵⁵

The Public Health Informatics Institute focuses on informatics workforce supply to public health.⁵⁶ The International Society for Computational Biology (ISCB) focuses on computational biology.⁵⁷ Likewise, the Society for Imaging Informatics and Medicine (SIIM) focuses on imaging informatics.⁵⁸ The Association for Computing Machinery (ACM) is the professional association for computer science.⁵⁹ The Medical Library Association (MLA) focuses on health science librarianship.⁶⁰

There are many specialty societies for healthcare professionals and most have some interest in informatics. For example, the American Medical Association (AMA) has several programs that mainly focus on running and maintaining physician practices, including the use of health IT.⁶¹ Likewise, the American Nurses Association (ANA) has an interest in informatics issues related to nursing.⁶² The Association of American Medical Colleges (AAMC), the professional organization for medical schools, is very active in informatics, as is the American College of Physicians (ACP), the professional society for internal medicine physicians, and the American Academy of Family Physicians (AAFP).⁶³-⁶⁵

Governmental Agencies

Although informatics is carried out at all levels of government, in the US it is predominantly an activity of the federal government. In the US, the Department of Health & Human Services (HHS) is the cabinet-level agency that is an umbrella for most of the important government agencies that involve HIT. The Office of the National Coordinator for Health Information Technology (ONC) reports directly to the Secretary of HHS and is not an agency per se. Other operating divisions under HHS include:

•National Institutes of Health (NIH)

•Agency for Healthcare Research & Quality (AHRQ)

•Centers for Medicare & Medicaid Services (CMS)

•Centers for Disease Control & Prevention (CDC)

•Health Resources & Services Administration (HRSA)

•Indian Health Service (IHS)

•Food and Drug Administration (FDA)

•Administration on Aging (AOA) ⁶⁶

Office of the National Coordinator for Health Information Technology (ONC). The ONC oversees the application of HIT, mostly focused on the adoption of EHRs. It led the implementation of the Health Information Technology for Economic and Clinical Health (HITECH) Act, which provided $30 billion funding through the American Recovery and Reinvestment Act (ARRA) in incentives for EHR adoption. Its main focus now is on standards, interoperability, HIE, and safety of EHRs and their clinical data.⁶⁷ The following are the broad goals of the 2015-2020 Federal Health IT Strategic Plan developed by ONC.⁶⁸ The specific objectives and strategies are outlined in detail in the plan displayed in table 1.1 on next page.

ONC initially established the Health IT Policy Committee (HITPC) and the Health IT Standards Committee (HITSC), but in the 2015 timeframe both committees were replaced by the Health Information Technology Advisory Committee (HITAC). HITAC recommends to the National Coordinator policies, standards, implementation specifications and certification criteria related to HIT.

There are many other US government agencies involved in aspects of health informatics.

The National Institutes of Health (NIH) is the premiere federal agency for biomedical research. One of its institutes is the National Library of Medicine (NLM). NLM serves as the nation’s, and really the world’s, medical library, but it is also the lead federal funder of research and training in biomedical informatics. The importance of the NLM was reaffirmed recently with the appointment of a new leader, and the incorporation of various data science initiatives within NHS into NLM.⁶⁹

Agency for Healthcare Research and Quality (AHRQ). The AHRQ is "the lead Federal agency charged with improving the quality, safety, efficiency, and effectiveness of health care for all Americans. As one of 12 agencies within the Department of Health and Human Services, AHRQ supports health services research that will improve the quality of health care and promote evidence-based decision making." This agency sets aside significant grant money to support healthcare information technology (HIT) research each year. AHRQ also maintains the National Resource Center for HIT, an extensive patient safety and quality section and an extensive HIT Knowledge Library with over 6,000 resources.⁷⁰

Centers for Medicare and Medicaid Services (CMS). CMS is responsible for providing care to 55.3 million Medicare (2015 data) and 69 million Medicaid patients (2013 data). To improve quality and decrease costs, CMS has information technology pilot projects in multiple areas, to include pay-for-performance demonstration projects that link payments to improved patient outcomes. They reimburse Medicare and Medicaid clinicians for Meaningful Use of certified EHRs. Several informatics-related projects will be discussed in later chapters.⁷¹

Table 1.1: Goals of the 2015-2020 Federal Health IT Strategic Plan

Centers for Disease Control and Prevention (CDC). Although not a primary information technology agency, the CDC has used HIT to promote population health-related issues. Among their programs of interest:

•Public Health Information Network (PHIN), covered in the chapter on public health informatics

•Human Genome Epidemiology Network (HuGENET ™ ) correlates genetic information with public health

•Family History Public Health Initiative is a web site that records family history information and encourages saving it in a digital format, so it can be shared. This is discussed more in the chapter on bioinformatics

•Public Health Image Library contains photos, images and videos on medical topics

•National Health and Nutrition Evaluation Survey (NHANE) program surveys about 10,000 US citizens every two years and shares the results with the public and researchers

•Geographic information systems (GIS) are also covered in chapter on public health informatics

•Podcasts, RSS feeds and apps on medical topics ⁷²

Health Resources and Services Administration (HRSA) is part of HHS with the primary mission of assisting medical care for the underserved and uninsured in the United States, particularly in rural areas. They support federally qualified health centers (FQHCs) and rural health centers (RHCs). HRSA supports grants for community health centers to include the installation and upgrades of health information technology. They have been a long-term grant supporter of telemedicine. On their web site, they post a variety of health-related data in the HRSA data warehouse. Searchable topics are presented with the ability to present as a table, chart, map or report.⁷³

National Committee on Vital and Health Statistics (NCVHS) is a public advisory body to the Secretary of Health and Human Services. It is composed of 18 members from the private sector who are subject matter experts in the fields of health statistics, electronic HIE, privacy/security, data standards and epidemiology. They have been very involved in advising the Secretary in matters related to the HealtheWay (Nationwide Health Information Network), HIPAA, interoperability and other important topics.⁷⁴

National Institute of Standards and Technology (NIST) is a physical science laboratory that is part of the U.S. Department of Commerce and serves to promote and verify measurements and standards. This federal agency makes EHR testing recommendations. The following is a list of some of the pertinent publications related to EHRs:

•(NISTIR 7741) NIST Guide to the Processes Approach for Improving the Usability of Electronic Health Records

•(NISTIR 7742) Customized Common Industry Format Template for Electronic Health Record Usability Testing

•(NISTIR 7743) Usability in Health IT: Technical Strategy, Research, and Implementation

•(NISTIR 7769) Human Factors Guidance to Prevent Healthcare Disparities with the Adoption of EHRs ⁷⁵

FEDERAL GOVERNMENT INITIATIVES

The federal government has maintained that HIT is essential to improving the quality of medical care and containing costs; two important aspects of healthcare reform. It is a major payer of healthcare with the following programs: Medicare/Medicaid, Veterans Health Administration, Military Health System, Indian Health Service and the Federal Employees Health Benefits Program. It is therefore no surprise that they are heavily involved in HIT and stand to benefit greatly from interoperability. Agencies such as Medicare/Medicaid and AHRQ conduct HIT pilot projects that potentially could improve the quality of medical care and/or decrease medical costs. The federal government has recognized the importance of technology in multiple areas and as a result has a federal chief technology officer and chief technology officer for HHS.

While the US government has been involved in many aspects of health informatics since the inception of the field, its role increased dramatically with the passage of the American Recovery and Reinvestment Act (ARRA) in 2009.

The most significant governmental initiative that affected the field of Informatics was the HITECH Act. This legislation impacted HIT adoption, particularly EHRs, as well as training and research. HITECH had five broad goals: (a) improve medical quality, patient safety, healthcare efficiency and reduce health disparities; (b) engage patients and families; (c) improve care coordination; (d) ensure adequate privacy and security of personal health information; (e) improve population and public health. Title IV and XIII of ARRA, known as the Health Information Technology for Economic and Clinical Health (HITECH) Act was devoted to funding of HIT programs. The HealthIT.gov website outlines the details of many of the HITECH programs.⁶⁷ Readers are encouraged to visit this web site often as HIT policy is subject to frequent change. In addition to the major programs, the following are also important initiatives that were part of HITECH:

•Privacy and HIPAA changes; to be discussed in chapter on privacy and security

•The National Telecommunications and Information Administration’s Broadband Technology Opportunities Program. This funded the National Broadband Plan discussed in the chapter on telemedicine

•Indian Health Services HIT programs

•Social Security Administration HIT programs

•Veterans Affairs (VA) HIT programs ⁷⁶

The Patient Protection and Affordable Care Act (PPACA) was enacted into law in March 2010 and is commonly known as the Affordable Care Act (ACA, or Obamacare). Its primary goals were to increase insurance coverage by expanding private and Medicaid coverage, to reduce healthcare costs, and to improve patient outcomes. The main focus of the legislation so far has been to increase health insurance coverage through the following mechanisms:

•Regulations that prevent insurers from discriminating against people with pre-existing conditions and prohibit lifetime caps on healthcare costs

•The requirement that all individuals have adequate insurance (and thus pay into the system while healthy)

•Subsidies to make that insurance affordable – for the lowest-income families, insurance is provided directly by Medicaid, while for those with higher incomes insurance is subsidized at rates that diminish with increasing income

Other areas within the ACA include:

•Patient Centered Outcomes Research Institute (PCORI) that funds patient-centered and comparative effectiveness research

•The CMS Innovation Center that evaluates healthcare models such as the Accountable Care Organization (ACOs)

•The National Prevention and Health Promotion Strategy

•Independence at Home Demonstration Projects

•Readmission Reduction Program to penalize healthcare systems with excessive readmissions

•Value based reimbursement to hospitals and physicians based on quality measures

•Scholarships and loan repayments for primary care physicians

•Grants for Health Centers to support HIT ⁷⁷

Medicare Access and CHIP Reauthorization Act (MACRA) of 2015

The main focus of this law was to replace the sustainable growth rate (SGR) formula, which was slated (but never implemented) to cut Medicare payment for physicians. MACRA also created a new framework for physician reimbursement, aiming to reward them for value and not volume of care provided. A number of other chapters in this book cover aspects of this subject. This new legislation is subject to policy change so should be interpreted with that context.⁷⁸

State Governments and HIT

There are a variety of state-based HIT initiatives, evaluating the adoption of technologies such as EHRs, HIE and e-prescribing. State Medicaid offices are anxious to conduct pilot projects aimed at reducing costs and/or improving quality of care.⁷⁹

International Governments and HIT

This chapter focuses primarily on US health informatics, but the reality is that this is an important and emerging field worldwide. Other countries have less expensive and less fragmented healthcare systems, but they also must deal with aging populations and rising chronic diseases. Meanwhile, technology continues to evolve unabated and in the case of mobile technology is quite affordable. They are therefore looking for healthcare solutions using cost-effective health information technology. Issues such as IT interoperability among European nations and certification are challenges all countries face. In the case of Europe and the European Union they refer to Health IT as eHealth and IT as information and communication technology (ICT).

The Digital Agenda for Europe (DAE) was created to enhance the economic condition in Europe and modernize all industries, to include healthcare. They have also established ICT-related cooperative efforts outside the EU. In 2013, they established ties with the US Department of Health and Human Services to further eHealth cooperation. The established Roadmap focuses on two high priority areas: standards development for interoperability and workforce development to increase skilled health IT workers in Europe. The timeline for this cooperative initiative was 18 months.⁸⁰ Multiple other international eHealth initiatives, collaborations and innovations are discussed in other chapters.

International health informatics is a mature sophisticated movement that is supported by multiple countries and international organizations such as the World Health Organization (WHO). The WHO fully supports eHealth with multiple programs and projects. One of their newest collaborations is the WHO Collaborating Centre in Consumer Health Informatics, established to help patients manage their own health. The most prominent international informatics organization is the International Medical Informatics Association (IMIA) that supports the International Journal of Medical Informatics. Several international conferences are held to collaborate and support health informatics research efforts. Other international medical informatics associations are discussed in the chapter on International Health Informatics.

PUBLIC-PRIVATE PARTNERSHIPS

National Academy of Medicine (NAM). This prominent organization was formerly known as the Institute of Medicine (IOM). It has published several highly influential reports on HIT over the last couple of decades. These reports have been widely cited, and have been very influential, influencing legislation, such as HIPAA and HITECH. They are available for download via PDF, and hard copies can be purchased on the National Academies Press website.

The first round of IOM reports came out in the 1990s, and into 2000. They focused mainly on identifying problems. The original report, The Computer-Based Patient Record, was published in 1991, and then revised in 1997. This was the first volume to bring together all the research identifying problems with paper records, the fact that they’re illegible, inefficient, and error prone, and really made the point that the computer-based record was vital to modern health care.⁸¹

Another influential report was For the Record, coming out in 1997, noting that, while there were benefits of EHRs, they would be compromised by inadequate privacy, security, and related problems. This report informed the details of the HIPAA legislation, which now are an integral part of modern US health care.⁸²

The Networking Health report that came out in 2000 looked at the then much less mature Internet and its role. Of course, this was before the era of smartphones and other ways that we interact online, including social media. But it noted the potential for networked health and addressed one issue at the time, which some people believed what was needed was a separate health Internet, and this report took a contrary view. Another important conclusion of this report was that the availability of the network was more important than its raw bandwidth, that is, the availability so that the Internet could be accessed any time with a reasonable amount of performance was more important than the pure speed of moving content, particularly images, around.⁸³

The IOM report that garnered the most press was, To Err Is Human. This report brought together research that had previously been done, noting that, first, medical errors are a lot more common than many believed, but even more important that the errors were a systems problem, that you couldn’t pin error problems on any one person, or any one segment of the health care industry. Many errors occurred when an error was made somewhere, and it propagated through the system, and the system was not able to identify the error before it happened.⁸⁴

These reports would not be that helpful if they just talked about the problems. As such, the next round of reports began to lay out solutions and started with a vision for a better health care system. The Crossing the Quality Chasm report was an early attempt to address issues of quality and the chasm between the way the health care system was and could be. This report argued that health care had to embody safety and quality throughout, that the system needed to be patient-centered and evidence-based, and this report developed a set of aims and rules for what they called high quality 21st century health care.⁸⁵

The Crossing the Quality Chasm report developed a set of aims for 21st century health care. It stated that health care should be safe, so avoiding injuries from care intended to help people. It should be affective, so that services provided based on tests and treatments that had justification in the scientific literature and avoiding care that would be unlikely to benefit individuals. Health care in the 21st century should be patient-centered, so respectful of patient’s preferences, needs, and values. It should be timely, so that individuals who need care can get it when they need it, and not have delays. Care should also be efficient, so avoiding waste of equipment, supplies, and energy. And it should be equitable, so everyone in the system was able to get care, and it was not denied to them based on any kind of personal characteristics, whether ethnicity, or socio-economic status, or other factors.

The Crossing the Quality Chasm report also laid out some rules for 21st century health care. It pointed out that patient needs and values should be the driver of variation in care, and not geography, or access to specialists, or other factors that really don’t relate to the individual. Care should be based on continuous healing relationships, so available 24/7, and by all modalities, including online. The patient should be the source of control of their care. There should be shared knowledge among all in health care, from the provider to the patient, to the institution, and so forth. There should be free flow of information and transparency, obviously, though, protecting individual privacy. There should be a focus on anticipating needs, rather than reacting to them, so trying to determine ahead of time how to best allocate resources, rather than react when resources are needed. And decision making should be evidence-based, based on science.

In 2003, Fostering Rapid Advances in Healthcare... was published under the guise of the need to foster rapid advances in health care. It called for demonstration projects that implemented the vision of the Quality Chasm report. It looked at some of the information technology issues. It noted that there was lack of interoperability of data, so that data was trapped in different silos. This was in an era where there were very few EHRs. However, we know, even in modern times, we still have this problem with interoperability of data and it being trapped in silos. To unlock information, we need standards and interoperability, so information can move between systems. This report also noted some of the research looking at the misalignment financial incentives when it came to IT, and that those who benefited from the system financially were not necessarily the same as those who were paying for the system.⁸⁶

Further delving into the harm problem of health care, the IOM came out with a report in 2004 on patient safety. There were many recommendations that came out of this report, a number of which focused on information technology. This report restated the case for the National Health Information Infrastructure, as it was called then, the idea that we have a national health information system, that we now call the Nationwide Health Information Network. It called for federal government leadership and public private partnerships. It reiterated the need for standards, so information could more easily move between systems with the patient. It also called for error reporting systems when they did occur that would be protected. Similar to the airline industry, individuals could disclose errors and not face punitive damages if they made attempts to rectify them. This report also made the case for a number of safety initiatives that are carried out in other industries, such as the airline industry, the nuclear power industry, things like adverse event analysis and near-miss analysis.⁸⁷

A further evolution in the view of the IOM reports started to look at using data to learn more about what health care does and try to improve it, to facilitate research. This led to the notion of the learning health system, the idea that, like other industries, we would capture data, and analyze it and attempt to improve what we do based on what we learned. The report that defined the learning health system was called, Knowing What Works in Health Care, recognizing that doing that requires capacity in information systems and people who know how to implement and use those systems. This report noted again, when EHRs were much less widely used, that the growing amount of data could aid the learning health care system.⁸⁸

Another workshop that came out of this report focused on the infrastructure needed for the learning health system and there was recognized the need for human capacity, including workforce development, including individuals trained in informatics.

By 2009, it was recognized that, even though there was much potential that had been recognized for HIT over a decade through these reports, that progress was not an as good as it could be. The report published in 2009, Computational Technology for Effective Health Care, noted that, even though there were a small number of exemplary institutions that were using IT well, we were failing at disseminating those benefits to other institutions. This report called for rethinking some of the approaches, such as focusing on clinical gains in an incremental fashion, not trying to revolutionize the system overnight, and aiming to make gains incrementally. It called for improving the coordination of health care, and improving the way it was financed, moving away from fee-for-service towards things like bundled payments. The report also called for avoiding the monolithic business-oriented systems that were evolving in health care institutions, and instead focusing on federations of systems that would provide value for patients and clinicians.⁸⁹

Further drilling down into the learning health care system led to the realization that there would need to be a digital infrastructure, that the system would need to build a structure of information—capture, and use, and sharing, and analysis—that would protect the rights of individuals. It would still enable the health care system function to perform efficiently. This report identified several themes for the digital infrastructure of the learning health care system and basically took an approach that there needs to be continuous learning. It needs to be integrated into the existing system. Considerations of scale were important, but also that the system must be decentralized and responsive to local needs. There would need to be low barriers to participate and minimizing complexity, all centered around a fabric of trust, so that patients, clinicians, and others would take part.

As more and more IT implementation occurred, especially after the HITECH Act, it was also increasingly recognized that, although IT systems could reduce error and harm, they could also increase it. In 2012, the IOM published its Health IT and Patient Safety report, noting that systems that could improve care might also introduce error and cause harm, if not designed and applied properly. This report called for federal oversight.⁹⁰

In late 2012, another IOM report came out, which brought a good deal of the vision and plans for implementation together. This report was called, Best Care at Lower Cost—The Path to Continuously Learning Health Care in America. The report started by reviewing the problems in health care, the required action that must be taken to decrease waste, estimated in this report to be $750 billion US dollars out of a $2.5 trillion system, and leading to 75,000 premature deaths. It draws on the analysis of Berwick and others on the sources of waste in the health care system, whether it’s services being provided that are not necessary, or any type of service, whether necessary or not, being inefficiently delivered. It notes that, for many things in the health care system, prices are too high relative to the cost. The US health care system also suffers from excess administrative costs, estimated to be as high as 30%. There are missed opportunities for prevention, not only prevention of disease, but prevention of complications once disease has developed and the problems of fraud in the health care system.⁹¹

In its vision, this report describes a number of components for the learning health care system, things like records being immediately updated and available for use by patients; care being delivered that has been proven reliable at the core, and then tailored to patient needs and preferences at the margins; the patient and family having their needs and preferences being a central part of the decision process; health care functioning as a team, and all of the team members being fully informed of each other’s activities at real time—so coordination of care; prices and total costs being fully transparent to all in the care process; incentives for payment being structured to reward outcomes in value, not volume of provided services; promptly identifying errors and correcting them; and routinely capturing patient outcomes, and using those to implement a system of continuous improvement.

The report notes that health care progresses from basic science understanding, which then becomes evidence that it actually works in humans, and then leads to care that’s delivered to patients. The current system has many missed opportunities, and wastes, and harm, so in translating from science to evidence, or evidence to care, or care to the patient experience, we have several problems. And instead, we should aim that there be a loop of science to evidence to care, and back informing science. And patients and clinicians and communities are part of that. And the missed opportunities, waste, and harm are minimal. All the above-mentioned IOM/NAM reports can be located and purchased on the National Academies Press web site.⁹²

BARRIERS TO HEALTH INFORMATION TECHNOLOGY ADOPTION

Up until the passage of the HITECH Act, the United States was behind many industrialized nations, in terms of per capita payments towards HIT. As of May 2017, CMS (Medicare) paid $9.5 billion for eligible professionals and $24.6 billion for eligible hospitals for adoption and meaningful use of EHRs. CMS (Medicaid) paid out $5.5 billion to eligible professionals and $11.9 billion to eligible hospitals.⁹³

Despite these large payments and good adoption statistics for inpatient and ambulatory EHRs, many problems still exist. Health information technology adoption has multiple barriers listed below and discussed in other chapters:

Inadequate time. This complaint is a common thread that runs throughout most discussions of technology barriers. Busy clinicians complain that they don’t have enough time to read or learn about new technologies or research vendors. They are also not reimbursed to become technology experts. They usually must turn to physician champions, local IT support, Regional Extension Centers or others for technology advice. A 2016 time-motion study noted that "for every hour physicians provide direct clinical face time to patients, nearly 2 additional hours is spent on EHR and desk work within the clinic day."³¹ We cannot expect busy clinicians to adopt future technologies until this issue is solved or improved.

Inadequate information. As pointed out earlier in the chapter, clinicians need information, not data. Current HIT systems are data rich, but information poor. This is discussed in detail in the healthcare data, information and knowledge chapter.

Inadequate expertise and workforce. For the United States to experience widespread HIT adoption and implementation, it will require education of all healthcare workers. Hersh emphasizes the need for a work force capable of leading implementation of the EHR and other technologies.⁹⁴ Educational offerings will need to be expanded at universities, community colleges and medical, nursing and pharmacy schools. There is a substantial difference between healthcare organizations, in terms of HIT sophistication. The first Work Force for Health Information Transformation Strategy Summit, hosted by the American Medical Informatics Association (AMIA) and the American Health Information Management Association (AHIMA) made several strategic recommendations regarding how to improve the work force.⁵³ AMIA has been the leader in Health Informatics education, with its 10 x 10 Program.⁹⁵ Their goal is to train 10,000 skilled workers over 10 years. The Community College Consortium graduated a significant number of students, but it is too early to know how successful job placement has been. HIT vendors are looking for applicants with both IT and clinical experience, in addition to good people skills and project management experience.⁹⁶ In addition to skilled informaticians; we will need to educate residents in training and faculty at medical schools, given the rapidly changing nature of HIT. The APA Summit on Medical Student Education Task Force on Informatics and Technology recommended that instead of CME, we need "longitudinal, skills-based tutoring by informaticians."⁹⁷ Family Medicine residency programs are generally ahead of other specialty training programs regarding IT training, promoting a longitudinal approach to IT competencies.⁹⁸

Inadequate cost and return on investment data. The literature on the economic aspects of HIT adoption and implementation is mixed and based on different assumptions and methods. An often-cited barrier is a mismatch between costs and benefits of HIT. The clinicians/providers bear the costs (and/or do the extra work), whereas hospitals/insurers/government reap the benefits. For example, clinicians must enter more